Abstract
BackgroundA better understanding of locally advanced cervical cancer (LACC) is mandatory for further improving the rates of disease control, since a significant proportion of patients still fail to respond or undergo relapse after concurrent chemoradiation treatment (CRT), and survival for these patients has generally remained poor.MethodsTo identify specific markers of CRT response, we compared pretreatment biopsies from LACC patients with pathological complete response (sensitive) with those from patients showing macroscopic residual tumor (resistant) after neoadjuvant CRT, using a proteomic approach integrated with gene expression profiling. The study of the underpinning mechanisms of chemoradiation response was carried out through in vitro models of cervical cancer.ResultsWe identified annexin A2 (ANXA2), N-myc downstream regulated gene 1 (NDRG1) and signal transducer and activator of transcription 1 (STAT1) as biomarkers of LACC patients’ responsiveness to CRT. The dataset collected through qPCR on these genes was used as training dataset to implement a Random Forest algorithm able to predict the response of new patients to this treatment. Mechanistic investigations demonstrated the key role of the identified genes in the balance between death and survival of tumor cells.ConclusionsOur results define a predictive gene signature that can help in cervical cancer patient stratification, thus providing a useful tool towards more personalized treatment modalities.
Highlights
A better understanding of locally advanced cervical cancer (LACC) is mandatory for further improving the rates of disease control, since a significant proportion of patients still fail to respond or undergo relapse after concurrent chemoradiation treatment (CRT), and survival for these patients has generally remained poor
Data from 2D-DIGE were subjected to Principal Component Analysis (PCA), allowing the identification of distinct spot signatures leading to two clusters of samples (Fig. 1a); this analysis showed a significant separation on plot between the samples belonging to S and R patient groups
The final list of proteins considered relevant to the aim of this study included Retinal dehydrogenase 1 (ALDH1A1), Rho GTPase-activating protein 1 (ARHGAP1), CALR, CASP14, Cytosolic non-specific dipeptidase (CNDP2), CP, GSN, HNRNPH1, HNRNPH2, HSP90AB1, HYOU1, LMNA, PCK2, PDCD4, SELENBP1, SFN, signal transducer and activator of transcription 1 (STAT1), SYNCRIP, TGM2, TINAGL1, VIM and XRCC5, which were over-represented in S compared to R patients, and annexin A2 (ANXA2), Mitotic checkpoint protein BUB3 (BUB3) and N-myc downstream regulated gene 1 (NDRG1) that showed a higher accumulation in biopsies of R patients compared to S patients (Additional file 1: Table S6)
Summary
A better understanding of locally advanced cervical cancer (LACC) is mandatory for further improving the rates of disease control, since a significant proportion of patients still fail to respond or undergo relapse after concurrent chemoradiation treatment (CRT), and survival for these patients has generally remained poor. Surgical treatment has the potential advantage of removing chemoradioresistant residual tumor foci, with a higher local control and possibly better survival, since resistance of cancer cells to CRT remains a major therapeutic drawback. In this regard, despite various microarray studies have been performed in advanced-stage cervical cancer patients to identify biological markers predictive of response to radiotherapy [10, 11], no definitive results have been reached yet and, more reliable biomarkers are warranted to further achieve predictive accuracy. Patient phenotyping would allow to predict the chance of response to this treatment, enabling patient allocation to personalized treatment procedures, with significant benefits to both patients and healthcare system
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